initialClustering {CIDER}R Documentation

Initial clustering

Description

Perform batch-specific initial clustering.

Usage

initialClustering(
  seu,
  batch.var = "Batch",
  cut.height = 0.4,
  nfeatures = 2000,
  additional.vars.to.regress = NULL,
  dims = seq_len(14),
  resolution = 0.6,
  downsampling.size = 50,
  verbose = FALSE
)

Arguments

seu

Seurat S4 object. Required.

batch.var

Character. One of the column names of 'seu@meta.data'. It is used to partition the Seurat object into smaller ones. Default: "Batch"

cut.height

Numeric. Height used to cut hirerchical trees. Default: 0.4

nfeatures

Number of high variance genes used. Default: 2000

additional.vars.to.regress

Additional variables to regress out. Needs to among column names of 'seu@meta.data'. Default: 'NULL'

dims

Number of dimension used for clustering. Passed to Seurat. Default: '1:14'

resolution

Resolution for clustering. Passed to Seurat. Default: 0.6

downsampling.size

Numeric. The number of cells representing each group. (Default: 40)

verbose

Print the progress bar or not. Default: FALSE

Value

Seurat S4 object with initial cluster information in 'initial_cluster' of meta.data.

See Also

getIDEr finalClustering


[Package CIDER version 0.99.1 Index]